code: def __init__(self, encoder):
      super().__init__()
  
      self.encoder = encoder
      self.block = self.encoder.block
      self.parallelize = self.encoder.parallelize
      self.main_input_name = encoder.main_input_name
  
file_path: lavis/lavis/models/pnp_vqa_models/pnp_unifiedqav2_fid.py
imports: import torch
  import torch.nn
  from lavis.common.registry import registry
  from lavis.models.base_model import BaseModel
  from lavis.common.utils import get_abs_path
  from transformers import T5Config, T5Tokenizer, T5ForConditionalGeneration
label_desc: Use image node_id 1 to create a new T5EncoderWrapper object from inherited base classes: torch.nn with example: obj = T5EncoderWrapper(encoder)